diff --git a/src/AnalysisPrograms/Recognizers/PteropusSpecies.cs b/src/AnalysisPrograms/Recognizers/PteropusSpecies.cs
index 20a608ca5..c85823e38 100644
--- a/src/AnalysisPrograms/Recognizers/PteropusSpecies.cs
+++ b/src/AnalysisPrograms/Recognizers/PteropusSpecies.cs
@@ -27,10 +27,8 @@ namespace AnalysisPrograms.Recognizers
     using System.IO;
     using System.Linq;
     using System.Reflection;
-    using System.Text;
     using Acoustics.Shared;
     using Acoustics.Shared.ConfigFile;
-    using Acoustics.Tools.Wav;
     using AnalysisBase;
     using AnalysisBase.ResultBases;
     using AnalysisPrograms.Recognizers.Base;
@@ -100,20 +98,20 @@ internal static RecognizerResults Gruntwork(AudioRecording audioRecording, Confi
             // get the common properties
             string speciesName = configuration[AnalysisKeys.SpeciesName] ?? "Pteropus species";
             string abbreviatedSpeciesName = configuration[AnalysisKeys.AbbreviatedSpeciesName] ?? "Pteropus";
+
+            // The following parameters worked well on a ten minute recording containing 14-16 calls.
+            // Note: if you lower the dB threshold, you need to increase maxDurationSeconds
             int minHz = configuration.GetIntOrNull(AnalysisKeys.MinHz) ?? 800;
             int maxHz = configuration.GetIntOrNull(AnalysisKeys.MaxHz) ?? 8000;
-
-            //var samples = audioRecording.WavReader.Samples;
-            double minDurationSeconds = configuration.GetIntOrNull(AnalysisKeys.MinDuration) ?? 0.2;
+            double minDurationSeconds = configuration.GetIntOrNull(AnalysisKeys.MinDuration) ?? 0.15;
             double maxDurationSeconds = configuration.GetIntOrNull(AnalysisKeys.MaxDuration) ?? 0.5;
             var minTimeSpan = TimeSpan.FromSeconds(minDurationSeconds);
             var maxTimeSpan = TimeSpan.FromSeconds(maxDurationSeconds);
-
             double decibelThreshold = configuration.GetDoubleOrNull(AnalysisKeys.NoiseBgThreshold) ?? 9.0;
 
             //######################
-            //2.Convert each segment to a spectrogram.
-            //double noiseReductionParameter = configuration.GetDoubleOrNull(AnalysisKeys.NoiseBgThreshold) ?? 0.1;
+            //2.Convert each segment to a spectrogram. Don't use samples in this recogniser.
+            //var samples = audioRecording.WavReader.Samples;
 
             // make a spectrogram
             var sonoConfig = new SonogramConfig
@@ -158,17 +156,18 @@ internal static RecognizerResults Gruntwork(AudioRecording audioRecording, Confi
                 ae.Name = abbreviatedSpeciesName;
             });
 
-            acousticEvents = FilterEventsForSpectralProfile(acousticEvents, sonogram.Data);
-
-            //var sonoImage = sonogram.GetImageFullyAnnotated("Test");
-            //var sonoImage = SpectrogramTools.GetSonogramPlusCharts(sonogram, acousticEvents, plots, null);
+            acousticEvents = FilterEventsForSpectralProfile(acousticEvents, sonogram);
 
-            //var opPath =
-            //    outputDirectory.Combine(
-            //        FilenameHelpers.AnalysisResultName(
-            //            Path.GetFileNameWithoutExtension(recording.BaseName), speciesName, "png", "DebugSpectrogram"));
-            //string imageFilename = audioRecording.BaseName + ".png";
-            //sonoImage.Save(Path.Combine(outputDirectory.FullName, imageFilename));
+            //Set following true if you want special debug spectrogram, i.e. with special plots
+            //In addition, standard spectrograms are produced when you set true in the config file, Towsey.PteropusSpecies.yml.
+            if (false)
+            {
+                //var image = sonogram.GetImageFullyAnnotated("Test");
+                var image = SpectrogramTools.GetSonogramPlusCharts(sonogram, acousticEvents, plots, null);
+                var opPath = outputDirectory.Combine(FilenameHelpers.AnalysisResultName(Path.GetFileNameWithoutExtension(audioRecording.BaseName), speciesName, "png", "DebugSpectrogram"));
+                string imageFilename = audioRecording.BaseName + ".png";
+                image.Save(Path.Combine(outputDirectory.FullName, imageFilename));
+            }
 
             return new RecognizerResults()
             {
@@ -184,61 +183,78 @@ internal static RecognizerResults Gruntwork(AudioRecording audioRecording, Confi
         /// Remove events whose acoustic profile does not match that of a flying fox.
         /// </summary>
         /// <param name="events">unfiltered acoustic events.</param>
-        /// <param name="spectrogramData">matrix of spectrogram values</param>
+        /// <param name="sonogram">includes matrix of spectrogram values.</param>
         /// <returns>filtered acoustic events.</returns>
-        private static List<AcousticEvent> FilterEventsForSpectralProfile(List<AcousticEvent> events, double[,] spectrogramData)
+        private static List<AcousticEvent> FilterEventsForSpectralProfile(List<AcousticEvent> events, BaseSonogram sonogram)
         {
+            double[,] spectrogramData = sonogram.Data;
             int colCount = spectrogramData.GetLength(1);
             var filteredEvents = new List<AcousticEvent>();
             foreach (AcousticEvent ae in events)
             {
                 int startFrame = ae.Oblong.RowTop;
                 int endFrame = ae.Oblong.RowBottom;
-                var subMatrix = DataTools.Submatrix(spectrogramData, startFrame, 0, endFrame, colCount - 1);
+
+                int maxBin = (int)Math.Round(8000 / sonogram.FBinWidth);
+
+                // get all the frames of the acoustic event
+                //var subMatrix = DataTools.Submatrix(spectrogramData, startFrame, 0, endFrame, colCount - 1);
+
+                // get only the frames from centre of the acoustic event
+                var subMatrix = DataTools.Submatrix(spectrogramData, startFrame + 1, 0, startFrame + 4, maxBin);
+
                 var spectrum = MatrixTools.GetColumnAverages(subMatrix);
+                var normalisedSpectrum = DataTools.normalise(spectrum);
+                normalisedSpectrum = DataTools.filterMovingAverageOLD(normalisedSpectrum, 11);
+                var maxId = DataTools.GetMaxIndex(normalisedSpectrum);
+                var maxHz = (int)Math.Ceiling(maxId * sonogram.FBinWidth);
 
-                // do test to determine if event has spectrum matching a Flying fox.
-                // TODO write method to determine similarity of spectrum to a true flying fox spectrum.
-                // There should be little energy in 0-600 Hz band.
-                // There should three peaks at around 1.5 kHz, 3 kHz and 6 kHz.
-                bool goodMatch = true;
-                if (goodMatch)
-                {
-                    filteredEvents.Add(ae);
-                }
-            }
+                // Do TESTS to determine if event has spectrum matching a Flying fox.
 
-            return filteredEvents;
-        }
+                // Test 1: Spectral maximum should be below 4 kHz.
+                int fourkHzBin = (int)Math.Round(4000 / sonogram.FBinWidth);
+                bool passTest1 = maxId < fourkHzBin;
 
-        /*
-            // example method
-            private static List<AcousticEvent> RunFemaleProfile(configuration, rest of arguments)
-            {
-                const string femaleProfile = "Female";
-                Config currentProfile = ConfigFile.GetProfile(configuration, femaleProfile);
-                Log.Info($"Analyzing profile: {femaleProfile}");
+                // Test 2: There should be little energy in 0-1 kHz band.
+                int onekHzBin = (int)Math.Round(1000 / sonogram.FBinWidth);
+                var subband1Khz = DataTools.Subarray(normalisedSpectrum, 0, onekHzBin);
+                double bandArea1 = subband1Khz.Sum();
+                double energyRatio1 = bandArea1 / normalisedSpectrum.Sum();
 
-                // extract parameters
-                int minHz = (int)configuration[AnalysisKeys.MinHz];
+                // 0.125  = 1/8.  i.e. test requires that energy in 0-1kHz band is less than average in all 8 kHz bands
+                // 0.0938 = 3/32. i.e. test requires that energy in 0-1kHz band is less than 3/4 average in all 8 kHz bands
+                // 0.0625 = 1/16. i.e. test requires that energy in 0-1kHz band is less than half average in all 8 kHz bands
+                bool passTest2 = !(energyRatio1 > 0.0938);
 
-                // ...
+                // Test 3: There should be little energy in 4-5 kHz band.
+                var subband4Khz = DataTools.Subarray(normalisedSpectrum, fourkHzBin, onekHzBin);
+                double bandArea2 = subband4Khz.Sum();
+                double energyRatio2 = bandArea2 / normalisedSpectrum.Sum();
+                bool passTest3 = !(energyRatio2 > 0.125);
 
-                // run the algorithm
-                List<AcousticEvent> acousticEvents;
-                Oscillations2012.Execute(All the correct parameters, minHz);
+                // TODO write method to determine similarity of spectrum to a true flying fox spectrum.
+                // Problem: it is not certain how variable the FF spectra are.
+                // In ten minutes of recording used so far, which include 14-15 obvious calls, there appear to be two spectral types.
+                // One type has three peaks at around 1.5 kHz, 3 kHz and 6 kHz.
+                // The other type have two peaks around 2.5 and 5.5 kHz.
 
-                // augment the returned events
-                acousticEvents.ForEach(ae =>
+                //if (passTest1)
+                //if (true)
+                if (passTest1 && passTest2 && passTest3)
                 {
-                    ae.SpeciesName = speciesName;
-                    ae.Profile = femaleProfile;
-                    ae.AnalysisIdealSegmentDuration = recordingDuration;
-                    ae.Name = abbreviatedSpeciesName;
-                });
+                    filteredEvents.Add(ae);
 
-                return acousticEvents;
+                    // draw DEBUG IMAGES
+                    if (true)
+                    {
+                        string name = "FF spectrum " + ae.SegmentStartSeconds + "s Frame" + startFrame + " maxHz" + maxHz;
+                        var bmp2 = GraphsAndCharts.DrawGraph(name, normalisedSpectrum, 100);
+                        bmp2.Save(Path.Combine(@"C:\Ecoacoustics\Output\BradLaw\FlyingFox\Towsey.PteropusSpecies", name + ".png"));
+                    }
+                }
             }
-            */
+
+            return filteredEvents;
+        }
     }
 }
diff --git a/src/AudioAnalysisTools/AcousticEvent.cs b/src/AudioAnalysisTools/AcousticEvent.cs
index 1c9c15252..02e51195f 100644
--- a/src/AudioAnalysisTools/AcousticEvent.cs
+++ b/src/AudioAnalysisTools/AcousticEvent.cs
@@ -1172,10 +1172,15 @@ public static List<AcousticEvent> GetEventsAroundMaxima(
                 // find start frame of current event
                 while (values[i] > thresholdValue)
                 {
+                    if (i <= 0)
+                    {
+                        break;
+                    }
+
                     i--;
                 }
 
-                startFrame = i;
+                startFrame = i + 1;
 
                 // find end frame of current event
                 i = maxFrame;
@@ -1186,7 +1191,7 @@ public static List<AcousticEvent> GetEventsAroundMaxima(
 
                 endFrame = i;
 
-                int frameDuration = endFrame - startFrame; // +1 ?????????????????
+                int frameDuration = endFrame - startFrame + 1;
                 if (frameDuration >= minFrames && frameDuration <= maxFrames)
                 {
                     double startTime = startFrame * frameOffset; // time in seconds