diff --git a/main.cpp b/main.cpp
index e4a3091..d13d750 100644
--- a/main.cpp
+++ b/main.cpp
@@ -554,7 +554,7 @@ int main(int argc, char *argv[])
             _("The kappa parameter of von Mises distribution"
               " (concentration);"
               " typically the strength of the wind direction");
-    opt.natural_kappa->required = YES;
+    opt.natural_kappa->required = NO;
     opt.natural_kappa->guisection = _("Dispersal");
 
     opt.anthro_kernel = G_define_option();
@@ -774,8 +774,9 @@ int main(int argc, char *argv[])
     else if (opt.natural_kappa->answer)
         config.natural_kappa = std::stod(opt.natural_kappa->answer);
 
-    config.anthro_kernel_type = opt.anthro_kernel->answer;
     config.use_anthropogenic_kernel = false;
+    if (opt.anthro_kernel->answer)
+        config.anthro_kernel_type = opt.anthro_kernel->answer;
     if (kernel_type_from_string(config.anthro_kernel_type) != DispersalKernelType::None)
         config.use_anthropogenic_kernel = true;
 
diff --git a/testsuite/test_r_pops_spread.py b/testsuite/test_r_pops_spread.py
index a335591..5567aae 100755
--- a/testsuite/test_r_pops_spread.py
+++ b/testsuite/test_r_pops_spread.py
@@ -263,6 +263,89 @@ def test_outputs_sei0(self):
         values = dict(null_cells=0, min=0, max=7.440, mean=0.947)
         self.assertRasterFitsUnivar(raster='stddev', reference=values, precision=0.001)
 
+    def test_natural_kernel_only(self):
+        """Check with only natural kernel (no anthropogenic kernel)"""
+        start = '2019-01-01'
+        end = '2022-12-31'
+        self.assertModule(
+            'r.pops.spread', host='host', total_plants='max_host', infected='infection',
+            average='average', average_series='average', single_series='single',
+            stddev='stddev', stddev_series='stddev',
+            probability='probability', probability_series='probability',
+            start_date=start, end_date=end, seasonality=[1, 12], step_unit='week',
+            step_num_units=1,
+            reproductive_rate=1, natural_dispersal_kernel='exponential', natural_distance=50,
+            natural_direction='W', natural_direction_strength=3,
+            random_seed=1, runs=5, nprocs=5
+        )
+        self.assertRasterExists('average')
+        self.assertRasterExists('stddev')
+        self.assertRasterExists('probability')
+        end = end[:4]
+        self.assertRasterExists('average' + '_{}_12_31'.format(end))
+        self.assertRasterExists('probability' + '_{}_12_31'.format(end))
+        self.assertRasterExists('single' + '_{}_12_31'.format(end))
+        self.assertRasterExists('stddev' + '_{}_12_31'.format(end))
+
+        ref_float = dict(datatype="DCELL")
+        ref_int = dict(datatype="CELL")
+        self.assertRasterFitsInfo(raster="average", reference=ref_float)
+        self.assertRasterFitsInfo(raster="stddev", reference=ref_float)
+        self.assertRasterFitsInfo(raster="probability", reference=ref_float)
+        self.assertRasterFitsInfo(
+            raster="single" + "_{}_12_31".format(end),
+            reference=ref_int
+        )
+        self.assertRasterFitsInfo(
+            raster="average" + "_{}_12_31".format(end),
+            reference=ref_float
+        )
+        self.assertRasterFitsInfo(
+            raster="probability" + "_{}_12_31".format(end),
+            reference=ref_float
+        )
+        self.assertRasterFitsInfo(
+            raster="stddev" + "_{}_12_31".format(end),
+            reference=ref_float
+        )
+
+        values = dict(null_cells=0, min=0, max=18, mean=0.447)
+        self.assertRasterFitsUnivar(raster='average', reference=values, precision=0.001)
+        values = dict(null_cells=0, min=0, max=100, mean=7.830)
+        self.assertRasterFitsUnivar(raster='probability', reference=values, precision=0.001)
+        values = dict(null_cells=0, min=0, max=6, mean=0.123)
+        self.assertRasterFitsUnivar(raster='stddev', reference=values, precision=0.001)
+
+    def test_minimal_parameters(self):
+        """Check with only minimal set of parameters (optional or with defaults)"""
+        start = '2019-01-01'
+        end = '2022-12-31'
+        self.assertModule(
+            'r.pops.spread', host='host', total_plants='max_host', infected='infection',
+            average='average', average_series='average', single_series='single',
+            stddev='stddev',
+            probability='probability',
+            probability_series='probability',
+            start_date=start, end_date=end,
+            natural_distance=50,
+            random_seed=1
+        )
+        self.assertRasterExists('average')
+        self.assertRasterExists('stddev')
+        self.assertRasterExists('probability')
+
+        ref_float = dict(datatype="DCELL")
+        self.assertRasterFitsInfo(raster="average", reference=ref_float)
+        self.assertRasterFitsInfo(raster="stddev", reference=ref_float)
+        self.assertRasterFitsInfo(raster="probability", reference=ref_float)
+
+        values = dict(null_cells=0, min=0, max=18, mean=2.260)
+        self.assertRasterFitsUnivar(raster='average', reference=values, precision=0.001)
+        values = dict(null_cells=0, min=0, max=100, mean=44.790)
+        self.assertRasterFitsUnivar(raster='probability', reference=values, precision=0.001)
+        values = dict(null_cells=0, min=0, max=0, mean=0)
+        self.assertRasterFitsUnivar(raster='stddev', reference=values, precision=0.001)
+
 
 if __name__ == '__main__':
     test()